ESM 244: Assignment 3, Task 1

Read in data

ca_counties <- read_sf(here("data", "ca_counties"), layer = "CA_Counties_TIGER2016") %>% 
  clean_names() %>% 
  select(name)

st_crs(ca_counties) # "EPSG",3857

## Coordinate Reference System:
##   User input: WGS 84 / Pseudo-Mercator 
##   wkt:
## PROJCRS["WGS 84 / Pseudo-Mercator",
##     BASEGEOGCRS["WGS 84",
##         DATUM["World Geodetic System 1984",
##             ELLIPSOID["WGS 84",6378137,298.257223563,
##                 LENGTHUNIT["metre",1]]],
##         PRIMEM["Greenwich",0,
##             ANGLEUNIT["degree",0.0174532925199433]],
##         ID["EPSG",4326]],
##     CONVERSION["Popular Visualisation Pseudo-Mercator",
##         METHOD["Popular Visualisation Pseudo Mercator",
##             ID["EPSG",1024]],
##         PARAMETER["Latitude of natural origin",0,
##             ANGLEUNIT["degree",0.0174532925199433],
##             ID["EPSG",8801]],
##         PARAMETER["Longitude of natural origin",0,
##             ANGLEUNIT["degree",0.0174532925199433],
##             ID["EPSG",8802]],
##         PARAMETER["False easting",0,
##             LENGTHUNIT["metre",1],
##             ID["EPSG",8806]],
##         PARAMETER["False northing",0,
##             LENGTHUNIT["metre",1],
##             ID["EPSG",8807]]],
##     CS[Cartesian,2],
##         AXIS["easting (X)",east,
##             ORDER[1],
##             LENGTHUNIT["metre",1]],
##         AXIS["northing (Y)",north,
##             ORDER[2],
##             LENGTHUNIT["metre",1]],
##     USAGE[
##         SCOPE["unknown"],
##         AREA["World - 85°S to 85°N"],
##         BBOX[-85.06,-180,85.06,180]],
##     ID["EPSG",3857]]

oil_spill <- read_sf(here("data", "oilspill"), layer = "Oil_Spill_Incident_Tracking_%5Bds394%5D") %>% 
  clean_names()

st_crs(oil_spill)  # "EPSG",3857

## Coordinate Reference System:
##   User input: WGS 84 / Pseudo-Mercator 
##   wkt:
## PROJCRS["WGS 84 / Pseudo-Mercator",
##     BASEGEOGCRS["WGS 84",
##         DATUM["World Geodetic System 1984",
##             ELLIPSOID["WGS 84",6378137,298.257223563,
##                 LENGTHUNIT["metre",1]]],
##         PRIMEM["Greenwich",0,
##             ANGLEUNIT["degree",0.0174532925199433]],
##         ID["EPSG",4326]],
##     CONVERSION["Popular Visualisation Pseudo-Mercator",
##         METHOD["Popular Visualisation Pseudo Mercator",
##             ID["EPSG",1024]],
##         PARAMETER["Latitude of natural origin",0,
##             ANGLEUNIT["degree",0.0174532925199433],
##             ID["EPSG",8801]],
##         PARAMETER["Longitude of natural origin",0,
##             ANGLEUNIT["degree",0.0174532925199433],
##             ID["EPSG",8802]],
##         PARAMETER["False easting",0,
##             LENGTHUNIT["metre",1],
##             ID["EPSG",8806]],
##         PARAMETER["False northing",0,
##             LENGTHUNIT["metre",1],
##             ID["EPSG",8807]]],
##     CS[Cartesian,2],
##         AXIS["easting (X)",east,
##             ORDER[1],
##             LENGTHUNIT["metre",1]],
##         AXIS["northing (Y)",north,
##             ORDER[2],
##             LENGTHUNIT["metre",1]],
##     USAGE[
##         SCOPE["unknown"],
##         AREA["World - 85°S to 85°N"],
##         BBOX[-85.06,-180,85.06,180]],
##     ID["EPSG",3857]]

exploratory interactive map in tmap showing the location of oil spill events included in the data

ggplot() +
  geom_sf(data = ca_counties) +
  geom_sf(data = oil_spill, size = .5)

tmap_mode("view")

## tmap mode set to interactive viewing

tm_shape(oil_spill) + 
  tm_dots()

Static chloropleth map in ggplot in which the fill color for each county depends on the count of inland oil spill events by county for the 2008 oil spill data

oil_spill_inland <- oil_spill %>% 
  filter(inlandmari %in% c("Inland")) %>% 
  group_by(localecoun) %>% 
  summarise(count = n())

## `summarise()` ungrouping output (override with `.groups` argument)

county_oil <- ca_counties %>% 
  st_join(oil_spill) %>% 
  group_by(name) %>% 
  summarise(count = n())

## `summarise()` ungrouping output (override with `.groups` argument)

ggplot() +
  geom_sf(data = ca_counties) +
  geom_sf(data = county_oil, aes(fill = count)) +
  theme_bw()

Citation:

• Oil spill data provided by: CA State Geoportal: Oil Sill Incident Tracking [ds394] https://gis.data.ca.gov/datasets/7464e3d6f4924b50ad06e5a553d71086_0/data